Last week Commissioner Moedas published a report on the direct impact that investing in innovation has on EU economy. While this analysis was being conducted, at Stromatolite we used 20 years of innovation experience – from earlier futures concepts for large multinationals such as Apple, Nike and Nokia, to the last 4 years of building a global community of 5000 innovators – to test some of our earlier observations and assumptions and put them into practice. In other words, we invested in hands-on building of an innovation ecosystem.
During this process over the past 15 months, we witnessed something extraordinary – the innovation toolkit we developed with EU research centres hit 1.5 million impacts on social media; 11 unique new product ideas using the toolkit were incubated to first level prototype, one patenting process was initiated in month 10; two new startups founded, the new R-IoT microboard has already been batch tested for production; and as a byproduct of the extremely fast knowledge transfer, several peer-reviewed papers and one book chapter were published. Two projects are now nominated for major international awards and several are being discussed with multinationals and global distributors for deployment.
Here is how we made this happen:
1) Place creativity at the heart of innovation.
Creative thinking is the fuel for an enthusiastic exchange of ideas. In our case the project is called #MusicBricks because music is our social glue. It attracts experts from far afield into a neutral space for an extremely fast knowledge transfer. The Music Industry provides an excellent template for experimentation in the new IoT-enabled innovation space: it thrives on big data; it relies on cloud services; it attracts communities; it provides fast feedback loops for experimentation; it allows for quick prototyping and cheap testing of technology ideas; and it allows to port tested ideas successfully to other industry verticals (if this last claim arouses suspicion, feel free to jump directly to point 7).
2) Enable an extremely fast knowledge transfer.
We build toolkits which interface between research and innovation communities. In January 2015 we set out to create the #MusicBricks toolkit by turning the excellence from EU music tech research centres into APIs, GUIs and TUIs (Tangible User Interfaces). By the end of May 2015, they were ready for deployment and testing with our community of creative developers and early adopters over challenges of accessibility, health and communication. By month 9 we had 11 product prototypes built with the toolkit, by month 10 the first patent being filed.
3) Set up open innovation IP parameters.
Our Consortium Agreement was completely rewritten to enable interfacing with Background IP, deployment of newly created Research IP with adopter-friendly licenses, and creation of a layer of Innovation IP to motivate the wider community of innovators and early adopters.
4) Bring the best brains into the room.
A range of different literacies of digital making such as those shared within ad hoc teams that form within innovation ecosystems, seldom lie exclusively within the domain of a single individual or organisation. We are privileged to have access to some of the most brilliant researchers and innovators from varied fields of expertise, age groups, gender, cultural backgrounds, skills and interests. We embedded #MusicBricks into our Music Tech Fest community platform, where we set out to unite art and science, and academia and industry in a space of common understanding. When our close community surpassed 4000 members, our call response rate registered 25% regular engagement. At our first creative testbed we achieved 33% female innovators. The healthy mix of knowledge and engagement makes for an extremely vibrant ideas ecosystem.
5) Get your hands dirty.
Our community do not read peer-reviewed papers to each other. They literally show each other how to do things. The experimental ‘hack’ is not simply an intellectual game, but a material practice – an act of thinking out loud, embodied in physical and working objects. IoT-enabled gesture-driven and audiovisual-signalling feedback loops are becoming sophisticated tools for communication in this context.
6) Give ample support to valuable ideas.
Regular supply of knowledge and funds are both key to enable growth of innovation ideas. Hitting knowledge barriers can seriously affect timely delivery: direct access to an expert is key at those times. We spent 662 hours in face-to-face, Slack and Skype conversations with our incubatees, and this investment generously paid off. Motivation quickly drops if cashflow stops, and efforts are diverted to alternative sources of income. We ensured microfunding was available for first level industry prototypes and partnered with local incubators to provide further support.
7) Plug ideas into a network.
Ideas do not exist in isolation. Within innovation ecosystems research and developer teams are able to place their findings into the hands of people who will test them to their limits, and situate theoretical and intellectual results within real world environments to adapt their tools and make them more flexible, more robust and ultimately more useful to a variety of markets. With creativity at the heart, at Stromatolite we are trained to understand the wider context of an application, and spot the next serendipitous ‘Post-It’ note discovery. From the beginning of our project, we were scanning the horizon to identify verticals and markets for lateral deployment. As an outcome of the patenting process initiated in month 10 of the project, we are in talks with a multinational in the forestry and agriculture sector with the aim to streamline their heavy machinery operations.
As Commissioner Moedas places emphasis on investment in innovation, we have demonstrated that by using these 7 core ingredients even modest investment in creative innovation can radically impact industry verticals. Think what you could achieve in a large scale pilot using these principles…
Aside from building Innovation Ecosystems through Stromatolite Innovation Lab and its spinoffs Music Tech Fest and #MusicBricks, Michela Magas is currently co-chairing Innovation Ecosystems Group for the EU Alliance of Internet of Things Innovation (AIOTI), and co-writing the CAF Innovation Advisory recommendations for the H2020 Work Programme 2018/2019.
The image above is from FindingSomEthingBondingSoUnding – a project which uses EEG readers and the R-IoT microboard to detect neurofeedback in reaction to gesture, incubated to first level prototype through the #MusicBricks project. #MusicBricks has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement 644871.
I was happy to see a proper mass market IoT product come out of the music tech community. Aether’s Cone is an intelligent combination of web service-connected product, meaningful cloud content driven by intelligent music systems and gesture-driven personalisation training (check out how it works). It belongs to the world as described in both Cory Doctorow’s fictional Makers and Chris Anderson’s living community of Makers. These visions reflect our current reality. But they are still missing one vital element. Once we design intelligent products which plug into the cloud and which are wonderfully trained to cater for our personal needs and preferences, the most innovative space will happen when we *jointly* connect via our products. This means not only via an awkward touch-screen (essentially button-pressing) application, but by using a broader range of gesture and signalling. The best we can do for our new products is not just to enable them to respond to us, but to *talk to each other* via a common platform. This is at the core of crowdmaking.
Which brings me to the main reason why our age is so revolutionary compared to anything we, as experiential beings, have witnessed in the past. Colleagues from some of the cutting edge innovation teams from EU industry speak to me of the era of “New Enlightenment” – access to vast amounts of new knowledge gathered from intelligent data systems, which drives new, well-informed behaviours. There is definitely some truth in this. However there is a major difference between our age and a historic movement which flourished as a reaction to the oppression of individual opinion in the Middle Ages. Aided, as ever, by a technological leap (in this case the invention of the printing press), and hence dominated by the written word, better-informed personal opinion became not only possible, but strongly encouraged. It became the foundation of our education system. Most western education systems still insist on *discouraging doodling and tinkering* in favour of the written word. We (rightly or wrongly) trust *only* the written word when it comes to assurances and justice. We still carry the written word ethos which praises individualism to the extent that it has generated entire cultures and economic systems based on encouraging individual progress above the common good.
Our age has highlighted the benefits of a different form of behaviour – one that encourages collective intelligence. Unlike the Enlightenment’s individualist drip-feeding of personal knowledge, connected communities of the – so called – “new era of enlightenment” usefully moderate and collectively produce torrents of valuable information. Ideas of sharing and moderation prove to be more effective and more valuable than individual accumulation. The social revolution is not inherent in the digital medium, but transpires from new behaviours afforded through connectivity.
This collective intelligence is already heavily fuelled by visual imagery – which is historically where our mark-making communications started. Despite the dominance of the written word in school, our children spend most of their time using visual and gestural communication via tablets and robotic toys. We know they are already better at combining *gesture – signal – image – word* than we could ever be with the limitations of our training.
Gesture and signalling offer a vast range of affordances which can bypass the awkwardness of language, the slowness of typing, and the limitations of cross-cultural spoken language. Just watch children from different linguistic backgrounds interact. Some of their methods are truly ingenious. They seamlessly integrate gesture and available props, showing that tools are a much richer field of communication than boring flat tablets.
Now give the child a Cone. My guess is that the child will pick up the Cone and turn the dial vigorously wanting to influence *your* experience of it (wicked or fun as that may be). Why? Because we have always communicated via our tools. Now, watch what happens when we connect them.
If you are going to send a rocket to the moon, you need to be very sure of every component and instrument that forms part of that expedition. Technology Readiness Levels (TRLs) are measures devised by NASA in the 1980s to assess the maturity of evolving technologies – devices, materials, components, etc. – that they use within their course of business. The idea is that when a new technology is first invented, it is not suitable for immediate application. New technologies are subjected to experimentation, refinement, and ongoing testing. Once the technology is sufficiently proven, it can be incorporated into the system – in this case, a spaceship.
There is a major distinction between digital applications which can drive the EU economy quickly and competitively in the global market, and the traditional techno-centric discourse which largely relies on the concept of TRLs.
The TRL model is driven by the degree of maturity requested from technology and is particularly suited to its original context. NASA typically deals with high-risk technologies that carry high development costs. It creates projects that are aimed at very few end users, and which yield important user data only after final deployment.
But rocket ships are not the technologies that drive modern economy. Most of what drives the EU economy are low-risk, cheap-to-deploy applications, which engage early adopters and generate data from users at early stages of deployment. These models require a broader set of parameters to account for the agile, iterative nature of technological innovation in the digital space.
A creative application will typically be low-risk, cheap to run (especially relative to rocket ships), easy to understand, and can potentially get millions of early adopters, even as an experimental proof-of-concept. This may account for the fact that the largest number of successfully-funded projects on Kickstarter in 2013 were developed in the music domain – a rise of 305% compared to the previous year. It is highly unlikely that someone will die from deploying music technology projects to fans / backers at early stages of development.
Yet early deployment will often guarantee a dedicated following with a vested interest in the project – people who will willingly contribute to the project, consider themselves privileged to be part of the select few who are “in the know”, and who can proudly display a sense of ownership of the invention for helping it get off the ground and become successful.
The appropriate way to measure the impact of these early adopter models would have to account for 1) the level of risk; 2) the number of potential early adopters; 3) potential to yield data from early adoption; and finally 4) the technology readiness. I propose we call them Market Adoption Readiness Models (MARLs).
For a potential investor, a large number of early adopters (and their substantial related datasets) have often proven to be sufficient incentives for investment and acquisition in early stages of development (which would traditionally occupy the space between the experimental TRL3 and more advanced TRL7). In the creative applications sector therefore, the market is extremely agile, with development of applications being cheap and typically low risk, and a great potential of investment and acquisition through clearly demonstrable social and economic benefits in early stages.
In addition to this, the agile nature of the digital market and the relatively cheap deployment of competitive applications requires active development and evolution of technologies via constant innovation and new iterations of products and systems. It is essential that the product constantly evolves, or else it will lose out to competition. It is important therefore to focus primarily on early deployment in order to maximise on the creative engagement with the tools by early adopter creative content maker communities. This ensures the potential for growth through feedback loops and iterative stages of active development, and capitalises on collaboration and agile and adaptive innovation for maximum market competitiveness.
For this reason I consider the MARLs model to be intrinsically associated with the disruptive nature of the Allternet, where continuous participation, constant innovation and creative engagement are encouraged via a series of open platforms.
Market Adoption Readiness Levels provide a framework for assessing technologies that may be creative and experimental, but usefully eliminate inertia, unnecessary delays, and creative paralysis. They generate conversation points and active engagement through early adoption, feedback and iteration. They leverage the ‘minimum viable product’ approach to digital innovation suited to an entrepreneurial environment where data is the primary currency.
This year, in order to gather a large amount of data about our solar system, a team of scientists and engineers have created a low cost, open source, open access, mass space exploration system called Pocket Spacecraft. Using Kickstarter, thousands of people have joined the project to create their own ‘minimum viable product’ expedition to the moon.
In 2014, even space exploration itself can be exempt from TRLs.
In his paper Mapping Digital Makers, Julian Sefton-Green defines digital making as the process of using digital technologies creatively in order to make new products or digital artefacts . The approach to this form of making has its roots in the world of computer programming, but although programming skills often form part of the process, concepts from art and design, engineering and problem solving are also significant components of the intellectual framework. Active engagement with digital tools contributes to an understanding of how digital media work, and in so doing both a more creative and a more active critical engagement with prevailing technological environments results. With an understanding of how digital technologies can make meaning for people comes opportunity for enterprise in creating new value and meeting market needs.
David Gauntlett’s Making is Connecting explores the ways in which digital making constructs participatory cultures that positively transform societies. Central to that process is the notion of play. Gauntlett uses Lego bricks as a practical, physical example of the kinds of processes that digital making encourage: the ability to create and re-create from simple building blocks. As a frequently improvisational and social activity, digital making includes trial-and-error and collaborative approach to learning. Digital making not only contributes to the making of games, but also emulates game-like thinking in its approach – seeking solutions, reaching goals and solving problems through exploration and experimentation.
Digital making is often expressed as ‘hacking’, which presumes a hands-on approach to re-using, reappropriating, remodelling and reinventing existing technologies in order to make new and previously unimagined ones. Those new technologies may be virtual, physical or some combination of the two, but the process of digital making that underpins the hacker activity is a productive and creative one that blurs the line between user and creator, producer and consumer, performer and audience. Creative processes from pre-digital media forms provide a range of metaphors with which to understand digital making: e.g. editing, composing, producing, developing. Gauntlett’s Lego example provides perhaps the best analogy, since digital making is an inherently iterative process, in the sense that everything that can be made in the digital environment can be remade and repurposed again.
Digital making not only retrieves and reinforces the agency of citizenry when it comes to culture and media, it also provides a uniquely fertile space for creative enterprise and entrepreneurship due to the abundance of raw materials, the removal of physical restrictions on creativity and the speed with which a new tool can be taken to market, tested, altered, revised and remade. Digital making is both creative engagement and empowering opportunity with a low entry barrier, low risk and potential for high rewards.
It’s helpful to think of the shift in patterns of media creation and consumption as not simply some new behaviours and approaches, but as representative of a complete generational shift. Digital paradigms for Generations X and Y were web access, content delivery and information consumption. Today, we are in the world of Generation C, who are instead focused on Creation, Curation, Connection and Community. According to a research report released by Google 90% of Generation C are Content Creators.
Following data showing that “the recording industry is making more money from fan-made mashups, lip-syncs and tributes on YouTube than from official music videos” (IFPI), some of the Creative Industries who had previously been reluctant to accept new ways of participation and co-creation of content, welcomed content creators as legitimate alternative routes to monetisation in content co-creation. According to Francis Keeling, global head of digital business for Universal Music Group:
“It’s a massive growth area. We’re very excited about the creativity of consumers using our repertoire and creating their own versions of our videos”
The Google report claims that 39% of Generation C are aged 35 years or above, thus dispelling the myth that Generation C are strictly young digital natives. Amongst those are professionals who are regular content creators, and 60-70% regularly curate online content. Generation C paradigms are therefore different from those of Generations X and Y: their priorities are web uploads, content creation and information curation.
In this new Generation C-dominated market, Creative SMEs are becoming leading cultural producers. Generation C content creators are active contributors to culture and major cultural influencers, who build followers and a critical mass, which in turn creates opportunities for monetisation. Creating culture is therefore important for business. Every content creator who is able to earn from their content is a micro-company, and therefore monetization of creative content is contributing to the rise of the numbers of Creative SMEs.
Apple reports that the iTunes App Store has generated over €11bn for creative developers since its launch in 2008. An equivalent, but open, agile and fast technology framework for content creators allowing a combination of virtual and tangible applications could contribute to a considerable profit for EU Creative SMEs, spearheading innovation in manufacturing, interaction and communication, and driving new markets and business models.
Creative SME Content Creators require tools based on open platforms which they can reuse, recycle and upcycle, suitable for agile development environments which allow ad-hoc creation and connectivity through mesh networks, and fast uploads into the cloud. The aim is to create a rich ecosystem which impacts on culture, society, employment, and economic profit.
In other words, Generation C are looking for their own Lego bricks. By creating Application Programming Interfaces (APIs), Graphical User Interfaces (GUIs) and Tangible User Interfaces (TUIs) that connect with existing bodies of data and digital cultural artefacts, we lower the barrier of entry to a world of content creators; we enable the kind of play that creates revenue for stakeholders right across the value chain; and we contribute to that participatory culture.
[co-authored by Andrew Dubber]
In 1935, Edwin Armstrong introduced his employers at RCA to his new radio broadcasting technology, Frequency Modulation. His employers saw FM as a legitimately groundbreaking technology, a massive improvement to existing broadcast systems, but also a disruptive innovation to their existing business models and their status quo. For the next 19 years, they lobbied government and fought successfully in the courts against the technology, driving Armstrong to poverty and extreme hardship.
A new technological ecosystem provides both opportunities and challenges for a society and to those interested in retaining the incumbent technological infrastructures. Those challenges are often legal in nature, partly because the law is a powerful mechanism of control and prevention of change – but also because by disrupting the ways in which we communicate, behave and make use of information, we often create case scenarios that lie outside those imagined as possible at the time the relevant laws are written. As a result, these challenges need to be identified, negotiated and managed if the disruptive technologies are to be harnessed for the good of society.
Legislation frameworks need to support innovation for the greater good. However, in order for innovation to take place, transgression of the letter of the law is often inevitable. That does not mean that ethical issues such as privacy, safety, fairness and the agency of individuals can be ignored – quite the opposite. Where legislation does not reflect the realities of the new technological environment, fairness and the interests of the greater good are often set at odds against the legal infrastructure of the status quo.
Innovations should be tested in terms of their capacity for emancipatory potential – not simply for economic stakeholders but for the participation of all stakeholders and citizens. The Swedish concept of ‘lagom’ (just enough) provides a useful guiding principle for business enterprise in the field. While there is clear urgency to innovate, invest and exploit in the field of IoT, a rapacious ‘gold rush’ mentality will do more harm than good.
Experiments with IoT need to consider perennial ethical principles – in terms of privacy, security, equality, labour exploitation, protection of the vulnerable, and so on – but it’s important to understand that the legal aspects and normative values have to be considered and reflected upon at a very early stage in the design and implementation cycle. IoT innovation is currently in its early experimental stage, but already it is challenging existing frameworks and regulatory systems that were designed to operate within a different ecosystem.
Dialogue between innovators and legislators needs to be ongoing, and focus on the ethical ‘first principles’ from which the laws arise, rather than from the rules themselves. Disruptive innovation will often be transgressive by nature, but it need not be at odds with what is good for society, culture and the economy.
Once again, Uber provides us with a very good case in point. The service is actively breaking new ground and as a result new legislations are already needed. London cab drivers traditionally require years of training and testing in “the knowledge” but that registration and testing process is seemingly made redundant by technological advances that use GPS. Arguably, the principle (safe passage, good service and fair prices to customers) still applies, but the mandated mechanism that ensures that principle (the knowledge) is no longer strictly required.
As a case study Uber is useful from an ethical and social perspective within the context of European policy. While Uber is massively disruptive, it has also been shown to be open to misuse of information and unethical practice by staff of the service. This is problematic because it adheres to a logic of capital that, like the industry it seeks to disrupt, prioritises the maximisation of shareholder return over social good.
It’s important for IoT innovation to begin from a moral, ethical and legal standpoint, as information carries legal, moral and ethical values and affordances – and especially because IoT technologies provide for communication without the immediate mediation of a human actor – even though that information may be used in a way that directly affects human experience.
Within Europe, we have, right at this moment, a unique opportunity at a time of significant change to engineer significant technological disruption in the interest of the greater societal good, and balance that interest with the need to incentivise innovation and investment in the IoT space. To do so requires that we favour ethics and the social good over the specific requirements of legislation that may no longer be entirely fit for purpose. In the case of Uber, while providing ethical and legal challenges, which need to be addressed, its model is also predicated on the idea that the company makes money if the drivers make money. In this respect, as a profit sharing participatory system, it also provides a case study in economic innovation.
As much as any social, political and economic factor, the standardisation of railway tracks throughout America in the mid 1800s contributed to the creation of a coherent multi-state nation. Communication, mobility and seamless transition were made possible with the advent of trans-national rail. Not just viable businesses, but entire towns and cities were built on the back of the single, consistent gauge railway and the Pacific Railway Act of 1863 that ensured it.
Likewise today, for the creation of successful and innovative business ecosystems within the frontier of the Allternet, it is necessary to build cohesive, interoperable protocols. These allow for creative, useful and experiential devices and services to be developed to run on them.
Protocols must be centred on easy to understand, layman-level classifications of network types and capabilities. Allternet protocols require clear and simple interfacing through APIs, graphical and/or tangible user interfaces (GUIs and TUIs) that give a high degree of flexibility and freedom. Certification can happen in a modular fashion. As with open source technologies, we can certify an element, people can develop it, and we pass that certification on through the system.
These protocols should not be locked to a particular operating system or proprietary environment. It’s crucial to preserve creative possibilities as well as incorporate open frameworks in the design process. Certification and licensing provides attribution for design inheritance (as with Open Product Licences). This degree of openness and simplicity provides for a variety of new business models and services that can be made available to potential content creators and participants.
Data provides transparency. For example, when using Uber, the passenger requesting a ride knows exactly where the cab is, has a clear idea how much the journey will cost and knows the make, model and licence plate of the car as well as what the driver looks like. For drivers, Uber provides data that reports traffic information, the best routes, highlights busy periods and ways in which drivers can maximise their revenue so they have greater agency as well as a clear basis for decision making about their own work.
Stakeholders provide choice. The creators of simple protocols are, metaphorically, laying railway tracks. The stakeholders and content creators build a wide variety of trains and ancillary services. They may create a luxury passenger car or a goods train. However, standardisation of the tracks is important, because otherwise there is no connectivity.
Sharing provides trust. If the track providers do not take too much revenue (if, for instance, they demand less than a quarter of profits generated by their use), then there is room for stakeholders to make money. This not only incentivises creativity and innovation in new uses of those tracks, but also establishes the necessary trust required to invest in building upon that infrastructure.
Transparency, choice and trust encourage participation. The people who take passengers down the tracks are the service providers. If it is made easy to build on those tracks, then anyone can use them. That in turn creates employment – or further entrepreneurship – that also contributes to that ecosystem. In other words, there is an opportunity for monetisation by contributing to the platform.
If, on the other hand, the contributor is not given the opportunity to make a profit or that profit is too small or risky to incentivise participation, then the platform itself will not make a profit. The Allternet provides a context for the creation of a non-exploitative service to both clients and contributors. Stakeholders view their contribution and involvement as a partnership with the platform.
Just as they did with the establishment of the standardised railway, new and unimagined types of businesses can flourish, and new communities can emerge and thrive, enabled by Allternet protocols.
In their 1977 short film Powers of 10, Charles and Ray Eames demonstrate that different kinds of understanding are possible at different orders of magnitude. When designing data-driven systems, it is crucial to analyse data at the human scale as well as at the mass aggregate scale.
Today we have a model for understanding data at different levels of magnitude: Google Maps. We can zoom in and out of geography, and are able to distinguish and analyse continents with a level of detail appropriate for the scale. That does not include minutiae such as streets, houses and parks. In that frame, we can identify data that is grouped at the level of Europe, Africa and so on – and we do not require more complex insights at that level. We zoom in to distinguish features such as cities and their geospatial relationships. We are able to orient ourselves with more and more levels of granularity, or we can zoom out again to get a sense of the overall picture.
At the human scale, there is a very different requirement of data mapping than there is at a global scale. As such, the notion of ‘zooming in’ provides a very good metaphor for how we should design intelligent data systems.
Data is not only stored in the cloud, it is also analysed in the cloud. Smart IoT systems use Big Data filtering, create ontologies and classifications in order to make sense of that data, consider the context of data usage and use AI to train systems to recognise patterns in data. The wealth of aggregate data accumulated by the Allternet provides, in itself, opportunities for understanding at a high level of analysis, but that analysis may not be relevant at the human scale.
In order for ‘Internet of Things’ projects to be validated, it is essential to run pilots deploying agent-driven applications. In this way, it will be possible to test, for instance, a ‘System of Systems’ in physical space, in relation to a scale comprehensible and useful to the people using the devices within that system. In this way, these projects and systems are contextualised and understood within the broader Allternet space.
There are those who advocate creating a system of systems in abstraction. There is another school of thought that believes we should start from the users. Neither of those two is better nor more important than the other. Instead, it’s about the rules or assumptions that can be made at each level. At the level of reconnaissance, there is a more abstract relationship with data which is about describing contours. At the level of the individual, the relationship is with the person and their specific needs and requirements. Not only are both valid, but there are multiple layers of understanding that can be reached at different levels of magnification.
It’s important not to make assumptions about somebody sitting on the street based on data that is mapped from the perspective of an altitude of 10,000 feet. When you’re sitting next to that person, you will have a very different understanding of what data is useful to you.
Designing data-driven systems is about creating truly intelligent systems that understand and appropriately respond to scale (as with the Powers of 10) – as well as to time, since data takes on different kinds of meaning over time. If you create one set of descriptors at a particular time, you will inevitably need to renew those descriptors when conditions change. The Allternet is, in this respect, like a living ecosystem.
As with data – so with ideas. An idea is always a result of particular affordances and parameters that are on offer at that particular point in time. In the case of EU-funded projects, this is usually mapped up front, rather than allowed to evolve. Any intelligences that we can draw from these projects change too. Because EU projects are locked in the first moment, they struggle to create a good business model. The project is cemented in the past before it has begun. Good business is always a living ecosystem. It needs to continually innovate in order to survive, keep ahead of competition, and reinvent itself.
Understanding data at scale (and over time) reflects the fact that the Allternet acts as a living ecosystem. From that adaptive, reactive and context-aware starting point, novel and disruptive IoT business models can be supported.
In 1954 Paul Rand, the great American artist and typographer, placed a full page advertisement in the New York Times using Morse code. His thinking was that while a million eyes might see the paper that morning, the only eyes that mattered were those of General Sarnoff, President of the RCA Corporation, whose early career had begun as a wireless operator for Marconi and who had revealed that his proudest moment had been as one of the first operators to pick up the distress call from the Titanic. Rand’s objective was to win the RCA Corporation’s lucrative advertising contract for his agency. Later that morning the agency received a call from General Sarnoff’s office asking for a meeting.
Intelligent, targeted one-off solutions, can create as much economic impact as mass produced, widely disseminated products. The important thing is to assess each case scenario on its own terms and remember that one is sometimes the biggest number. The widespread distribution of the New York Times meant it was the ideal platform for Paul Rand’s innovative piece of communication design. In terms of modern economy, distribution platforms are a priority for enabling businesses targeting equally one or many stakeholders.
In one of the most rapidly changing sectors of the creative industries – the music industry – digitisation has given us the concept of the Long Tail. 10 years ago it became apparent that digital platforms made audio file storage and distribution cheap, and that for a digital platform selling 1M copies of a famous artist’s track was equally as lucrative as 1M artists selling a single download only. If 1M artists convinced their mothers to buy their record too, their joint sales instantly doubled to 2M. No wonder social networking recommendations became the main target for media publishers.
For the EU economy, 1M micro-companies creating enough wealth to make a decent living are equally important as one global brand generating millions in revenue. As well as creating impact by targeting just one stakeholder, individual producers can create global impact, at any scale, providing all their products are accessible via a common platform.
Different scales matter also when devising innovative solutions. It is equally as important to provide solutions for the basic level functionality (“if I press here, x will happen”), as it is for the working level (“if I streamline this service, my workflow will improve”), and high level challenges (“if we adopt a different approach, we will create a new market and benefit a new sector of society”). A Sharing Economy platform enables crowdmaking participants who may have ideas for grand societal changes, but not the tools to execute them, to join up with those good at small scale solutions, able to work from the ground up.
Innovative ideas are not there to attract private funding and create a number of temporary startup employment positions in view of “scaling fast”. Often such methods create merely a stop-gap for unemployment, but no real long-term sustainable business solution. “Fail fast and fail often” may be the motto for the “winner takes all” culture of American Capitalism, but models based on the principles of Sharing Economy allow for many small businesses to make a good living by staying small and sustainable, as well as businesses to grow organically, at the right time and for the right reasons.
Many EU regions pride themselves on small family businesses, which in modern terms create the Long Tail of the EU economy. We should not therefore encourage these to scale too rapidly and fail fast, but instead create enabling sharing technology platforms which facilitate business operations at any scale, and where even bespoke, customised one-offs can benefit from the common market place.
Real, sustainable innovation exists at the grass roots. As Dubber keeps telling me, our job is not to predict the future, but to jointly invent it.